US8275181B2 - Method for tracking of contrast enhancement pattern for pharmacokinetic and parametric analysis in fast-enhancing tissues using high-resolution MRI - Google Patents
Method for tracking of contrast enhancement pattern for pharmacokinetic and parametric analysis in fast-enhancing tissues using high-resolution MRI Download PDFInfo
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Definitions
- the present invention relates to a system and method for use with medical imaging and, more particularly to a system and method for obtaining and analyzing images from tissues which exhibit fast uptake of a contrast agent.
- prostate cancer is a usual object for many research studies.
- the appropriate tumor localization and staging are very important for determining the best choice of treatment.
- the most common diagnostic methods for prostate cancer are transrectal ultrasound and conventional magnetic resonance imaging (MRI). Unfortunately, these methods are not always able to differentiate and characterize the cancerous and healthy prostate tissues.
- DCE dynamic contrast enhanced
- the multi-slice images are acquired before, and during, contrast agent infusion. Subsequently, signal intensity versus time curves are analyzed using appropriate models for quantitative assessment of permeability and microvasculature of healthy and cancerous tissues. Those models rely on pixel-by-pixel analysis and high-spatial resolution of images, which are necessary to avoid volume averaging of contrast enhancement patterns. However, the high-spatial resolution poses some limitations on temporal resolution (i.e., how fast images can be taken).
- vascular permeability vascular permeability
- V extracellular space or volume
- the present invention addresses the above and other issues by providing a system and method for providing a high-resolution pharmacokinetic analysis for calculation of tissue parameters for fast-enhancing tissues such as prostate tissue.
- the invention involves a method for performing a high-resolution pharmacokinetic analysis for calculation of tissue parameters for a fast-enhancing tissue.
- the method includes obtaining mask image data of the fast-enhancing tissue when the fast-enhancing tissue is in a steady state condition, obtaining a time series of image data of the fast-enhancing tissue when the contrast agent is flowing in the fast-enhancing tissue, and increasing a spatial resolution of the time series of image data using the mask image data to obtain a time series of increased spatial resolution image data.
- the method further includes performing a pharmacokinetic analysis of the increased spatial resolution image data to obtain data including at least one pharmacokinetic parameter that characterizes the fast-enhancing tissue, providing a multi-parameter look-up table derived from a combination of two or more pharmacokinetic parameters, and providing a display including the at least one pharmacokinetic parameter or a parametric image, the parametric image being derived from the multi-parameter look-up table.
- the steady state condition is before injection of a contrast agent, or after injection of the contrast agent.
- the fast-enhancing tissue includes prostate tissue.
- the mask image data is obtained from a high-spatial resolution scan
- the time series of image data is obtained from a low-spatial resolution dynamic scan.
- the mask image data and the time series of image data are obtained using the same repetition time, flip angle, and echo time, and the mask image data and the time series of image data each include the same anatomical volume.
- increasing a spatial resolution of the time series of image data comprises combining low- and high-spatial resolution image data.
- combining the low- and high-spatial resolution image data includes transforming the low- and high-spatial resolution image data to a spatial frequency domain using Fourier transformation, and combining each of a series of low spatial frequencies of the low-spatial resolution images with high spatial frequencies of the high-spatial resolution image to form a complete spatial frequency volume.
- performing a pharmacokinetic analysis of the increased spatial resolution image data comprises applying an analysis model to the increased spatial resolution image data.
- the invention involves a program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for performing a high-resolution pharmacokinetic analysis for calculation of tissue parameters for a fast-enhancing tissue.
- the method steps include obtaining mask image data of the fast-enhancing tissue when the fast-enhancing tissue is in a steady state condition, obtaining a time series of image data of the fast-enhancing tissue when the contrast agent is flowing in the fast-enhancing tissue, and increasing a spatial resolution of the time series of image data using the mask image data to obtain a time series of increased spatial resolution image data.
- the method steps further include performing a pharmacokinetic analysis of the increased spatial resolution image data to obtain data including at least one pharmacokinetic parameter that characterizes the fast-enhancing tissue, providing a multi-parameter look-up table derived from a combination of two or more pharmacokinetic parameters, and providing a display including the at least one pharmacokinetic parameter or a parametric image, the parametric image being derived from the multi-parameter look-up table.
- the steady state condition is before injection of a contrast agent, or after injection of the contrast agent.
- the fast-enhancing tissue includes prostate tissue.
- the mask image data is obtained from a high-spatial resolution scan
- the time series of image data is obtained from a low-spatial resolution dynamic scan.
- the mask image data and the time series of image data are obtained using the same repetition time, flip angle, and echo time, and the mask image data and the time series of image data each include the same anatomical volume.
- increasing a spatial resolution of the time series of image data comprises combining low- and high-spatial resolution image data.
- combining the low- and high-spatial resolution image data includes transforming the low- and high-spatial resolution image data to a spatial frequency domain using Fourier transformation, and combining each of a series of low spatial frequencies of the low-spatial resolution images with high spatial frequencies of the high-spatial resolution image to form a complete spatial frequency volume.
- performing a pharmacokinetic analysis of the increased spatial resolution image data comprises applying an analysis model to the increased spatial resolution image data.
- the invention involves a system for performing a high-resolution pharmacokinetic analysis for calculation of tissue parameters for a fast-enhancing tissue.
- the system includes means for obtaining mask image data of the fast-enhancing tissue when the fast-enhancing tissue is in a steady state condition, means for obtaining a time series of image data of the fast-enhancing tissue when the contrast agent is flowing in the fast-enhancing tissue, and means for increasing a spatial resolution of the time series of image data using the mask image data to obtain a time series of increased spatial resolution image data.
- the system further includes means for performing a pharmacokinetic analysis of the increased spatial resolution image data to obtain data including at least one pharmacokinetic parameter that characterizes the fast-enhancing tissue, means for providing a multi-parameter look-up table derived from a combination of two or more pharmacokinetic parameters, and means for providing a display including the at least one pharmacokinetic parameter or a parametric image, where the parametric image is derived from the multi-parameter look-up table.
- FIG. 1 is an illustrative plot of contrast agent concentration versus time, according to one embodiment of the invention.
- FIG. 2 is an illustrative block diagram of a method for combining low- and high-spatial resolution image data, according to one embodiment of the invention.
- FIG. 3 is an illustrative k-space or spatial frequency diagram based on the combined low- and high-spatial resolution image data, according to one embodiment of the invention.
- FIG. 4 is an illustrative original low-spatial resolution image (128 ⁇ 128 voxels) of a prostate in an early enhancement phase, according to one embodiment of the invention.
- FIG. 5 is an illustrative original high-spatial resolution image (256 ⁇ 256 voxels) of a prostate before contrast agent injection, according to one embodiment of the invention.
- FIG. 6 is an illustrative original image of the prostate of FIG. 4 with improved spatial resolution (256 ⁇ 256 voxels) after application of the combining technique using the high-spatial resolution pre-contrast image of FIG. 5 .
- FIG. 7 is an illustrative colored permeability image of the prostate obtained from a pharmacokinetic analysis using a dynamic series of images with an original low-spatial resolution image (128 ⁇ 128 voxels), according to one embodiment of the invention.
- FIG. 8 is an illustrative colored permeability image of the prostate obtained from a pharmacokinetic analysis of a dynamic series of images with improved spatial resolution (256 ⁇ 256 voxels), according to one embodiment of the invention.
- FIG. 9A is an illustrative multi-parameter look-up table, according to one embodiment of the invention.
- FIG. 9B is an illustrative parametric image of a prostate corresponding to the multi-parameter look-up table of FIG. 9A .
- FIG. 10 is an illustrative colored parametric image of the prostate obtained from a pharmacokinetic analysis with further application of a multi-parameter look-up table using a dynamic series of images with the original low-spatial resolution (128 ⁇ 128 voxels), according to one embodiment of the invention.
- FIG. 11 is an illustrative colored parametric image of the prostate obtained from a pharmacokinetic analysis with further application of a multi-parameter look-up table using a dynamic series of images with improved spatial resolution (256 ⁇ 256 voxels), according to one embodiment of the invention.
- FIG. 12 is an illustrative flow diagram of a computer-implemented method for tracking of contrast enhancement pattern for pharmacokinetic and parametric analysis in fast-enhancing tissues using high-resolution magnetic resonance imaging, according to one embodiment of the invention.
- Enhancement patterns in tissues are mainly determined by the blood flow to the tissue and by the vascular permeability of the tissue vessels. For pharmacokinetic analysis and calculation of physiologic parameters, it is necessary to separate the flow and permeability contributions. Separating the flow and permeability contributions is only possible if the enhancement kinetics can be monitored with sufficient temporal resolution. As previously mentioned, dynamic imaging in general may not provide sufficient temporal resolution to monitor such rapid enhancement behavior. Low-resolution magnetic resonance (MR) images (with a matrix of 128 ⁇ 128 voxels or lower) have been previously employed to examine such fast enhancement behavior. However, this method causes the image voxels (i.e., volume elements) to be large, and volume-averages the enhancement patterns in the image voxels.
- MR magnetic resonance
- the present invention includes a system and method for combining high temporal and high-spatial resolution information acquired during two different phases of the magnetic resonance (MR) examination and enables post-processing using dynamic models with a high-spatial resolution (e.g., a matrix of 256 ⁇ 256 voxels or better), and a high temporal resolution (e.g., thirty seconds or faster).
- a high-spatial resolution e.g., a matrix of 256 ⁇ 256 voxels or better
- a high temporal resolution e.g., thirty seconds or faster.
- an illustrative plot 100 of contrast agent concentration (C(t)) 105 versus time (t) 110 is shown.
- the concentration C(t) 105 subsequently exhibits a relatively quick decrease, which is indicative of malignant tissue.
- high-spatial resolution image data of the tissue can be obtained before, or well after, injection of the contrast agent, since the corresponding low temporal resolution does not result in a significant loss of information.
- the high-spatial resolution image data can be acquired with more than one number of acquisitions, which improves the quality of the image by reducing noise.
- high temporal resolution data is needed to capture the dynamic properties of the tissue.
- a consequence of obtaining high temporal resolution data is that it must be obtained at a lower spatial resolution.
- high-resolution image data which also captures the dynamic properties of the tissue, can be obtained.
- an illustrative block diagram of a method for combining low- and high-spatial resolution image data is shown.
- a set of high-spatial resolution images 200 covering a suspicious body volume is acquired (via an MRI machine) before injection of a contrast agent into the suspicious body volume.
- the high-spatial resolution images are acquired well after the injection of the contrast agent (e.g. 8-9 minutes after the injection for the prostate), when the tissue has returned to a steady state condition.
- a set of low resolution dynamic scans 210 a - 210 n is acquired with a desired time resolution.
- Both sets of images typically cover the same anatomical volume, and should be obtained using the same scan parameters, such as repetition time (TR), flip angle, and echo time (TE).
- the low- and high-spatial resolution data 210 a - 210 n , and 200 respectively, can be combined using various techniques to convert the low-spatial resolution dynamic scans 210 a - 210 n into high-spatial resolution images 220 a - 220 n.
- One possible approach for combining the low- and high-spatial resolution data involves the keyhole method (See e.g., J. J. van Vaals, M. E. Brummer, W. T. Dixon, H. H. Tuithof, H. Engels. Key-hole method for accelerating imaging of contrast agent uptake. J. Magn. Reson. Imaging, 3, pp 671-675, 1993, incorporated herein by reference).
- the keyhole technique all of the image sets 200 , 210 a - 210 n are transformed to the spatial frequency domain (k-space) using the Fourier transformation, as shown in FIG. 3 .
- the Fourier transform relates each point in k-space to a spatial domain MRI image.
- the efficient Fast Fourier Transform (FFT) can be used when the image matrices are symmetric.
- a k-space or spatial frequency diagram based on the combined low- and high-spatial resolution image data is shown.
- the k-space is divided into a central section 310 , which represents the low-spatial frequencies, and an outer section 300 , which represents the high-spatial frequencies.
- the central section is repeatedly acquired during contrast arrival from the data sets 210 a - 210 n .
- the outer section 300 is acquired from the data set 200 .
- each time frame e.g.
- dynamic images 220 a - 220 n is generated by combining a different central section 310 , from one of the data sets 210 a - 210 n , with the same outer section 300 from the data set 200 , to form a complete k-space volume.
- new sets of dynamic images 220 a - 220 n are created by combining the low-spatial frequency data of low-spatial resolution dynamic images 210 a - 210 n with the high-spatial frequency data of the high-resolution pre-contrast image set 200 .
- the dynamic images can then be used for an accurate and reliable pharmacokinetic analysis, and for calculation of tissue parameters such as vascular permeability (k-trans) and extracellular space (V).
- tissue parameters such as vascular permeability (k-trans) and extracellular space (V).
- the dynamic images can also be used as an aide for diagnosing tissue.
- FIG. 4-8 in one embodiment, various low- and high-spatial resolution images of the prostate are shown, which illustrate various benefits that are derived from the present system and method.
- the high-spatial resolution image has a 256 ⁇ 256 ⁇ 16 matrix (with 0.625 ⁇ 0.625 ⁇ 4 mm voxels) versus a 128 ⁇ 128 ⁇ 32 matrix (with 1.25 ⁇ 1.25 ⁇ 4 mm voxels) for high-temporal resolution dynamic images, and both sets cover the same anatomical volume of 16 ⁇ 16 ⁇ 64 cm.
- FIG. 4 illustrates an original low-spatial resolution image (128 ⁇ 128 voxels) of the prostate in an early enhancement phase. As can be seen, the level of detail is relatively poor.
- FIG. 5 illustrates an original high-spatial resolution image (256 ⁇ 256 voxels) of the prostate before contrast agent injection.
- FIG. 6 illustrates the same image of the prostate as in FIG. 4 , but with improved spatial resolution (256 ⁇ 256 voxels) after application of the combining technique using the high-spatial resolution pre-contrast image of FIG. 5 , according to the invention, and as previously described.
- FIG. 7 illustrates a permeability image of the prostate obtained from a pharmacokinetic analysis using the dynamic series of images with the original low-spatial resolution (128 ⁇ 128 voxels) ( FIG. 4 ).
- FIG. 8 illustrates a permeability image of the prostate obtained from a pharmacokinetic analysis of the dynamic series of images with improved spatial resolution (256 ⁇ 256 voxels).
- FIG. 8 illustrates a permeability image of the prostate obtained from a pharmacokinetic analysis of the dynamic series of images with improved spatial resolution (256 ⁇ 256 voxels).
- the direct pharmacokinetic parameters e.g. permeability and extracellular space
- the n-dimensional space of the chosen n parameters span from minimal to maximal values.
- the n-dimensional space can be divided into two or more desirable sub-spaces, where each sub-space is assigned different color.
- a parametric image of the tissue can be created and displayed based on the tissue parameters and the corresponding multi-parameter look-up table.
- the voxels with different parameter sets will be assigned the corresponding sub-space color.
- n n pharmacokinetic parameters
- actual voxels in a real dataset can be colored according to corresponding pharmacokinetic parameters and the corresponding multi-parameter look-up table.
- the multi-parameter look-up table is typically derived from the knowledge of the parametric value (and the combinations of these parametric values) in two or more tissues that are intended to be differentiated.
- the multi-parameter look-up table therefore, does not entail the use of a mathematical function. Instead, the look-up table is defined by customized areas that are assigned to an output color and/or intensity.
- Areas 900 and 910 correspond to combinations of permeability (ranges from 0-10 min ⁇ 1 ) and extracellular volume fraction (ranges from 0-1) of benign 900 and malignant 910 prostate tissues.
- the malignant areas 910 are manually defined (colored) as red, and the normal/benign areas 900 are manually defined (colored) as blue.
- An optional intermediate permeability/EVF combination 905 is manually defined (colored) as green.
- FIG. 9B is an example of a parametric image after implementation of pharmacokinetic analysis. Every processed voxel in FIG. 9B is colored based on a corresponding permeability/EVF pair obtained from the multi-parameter look-up table of FIG. 9A . Voxels of FIG. 9B with a permeability/EVF pair corresponding to the red (malignant) region 910 are colored red, and voxels with a permeability/EVF pair corresponding to the blue benign) region 900 are colored blue.
- a colored parametric image of the prostate obtained from a pharmacokinetic analysis with further application of a multi-parameter look-up table is shown.
- the parametric image of the prostate based on pharmacokinetic analysis results from using a dynamic series of images with the original low-spatial resolution (128 ⁇ 128 voxels).
- FIG. 11 in one embodiment, another colored parametric image of the prostate obtained from a pharmacokinetic analysis with further application of a multi-parameter look-up table is shown.
- the parametric image of the prostate based on pharmacokinetic analysis results from using dynamic series of images with improved spatial resolution (256 ⁇ 256 voxels).
- FIG. 12 a flow diagram of a method (which can be computer-implemented) for tracking of contrast enhancement pattern for pharmacokinetic and parametric analysis in fast-enhancing tissues using high-resolution magnetic resonance imaging is shown.
- the computer-implemented method is implemented using a typical computer system coupled to and controlling an MRI system.
- the computer system can be any computer system that includes a processor, memory (e.g. random access memory (RAM)), a mass storage device (e.g., a hard disk), and a display (e.g., a monitor).
- RAM random access memory
- the method in one embodiment, is a computer program that is stored on the mass storage device, loaded into RAM, executed on the processor, and displays obtained data on the monitor.
- the method includes obtaining first, mask image data of tissue when the tissue is in a steady state condition (Step 1200 ).
- a time series of second image data of the tissue when a contrast agent is present (flowing) in the tissue is obtained (Step 1210 ).
- a spatial resolution of the second image data is then increased using the first image data to obtain a time series of increased spatial resolution image data (Step 1220 ).
- a pharmacokinetic analysis of the increased spatial resolution image data is performed to obtain data including at least one parameter, which characterizes the tissue (Step 1230 ).
- a display in then provided, which includes the pharmacokinetic parameters or a parametric image based on a multi-parameter look-up table derived from the combination of two or more pharmacokinetic parameters (Step 1240 ).
- the parametric image can be provided on a display screen of a computer, or on a hard copy print out, for example.
- RIGR Reduced-encoding by Generalized-series Reconstruction
- RIGR uses a set of non-Fourier basis functions for dynamic image reconstruction.
- this model estimates the unmeasured (high-spatial-resolution) parts of the dynamic images by transforming the k-space image onto a set of constrained sinusoidal basis functions, whereas the keyhole technique is limited by the number of dynamic encodings measured (See, e.g.; A. G. Webb, Z. P. Liang, R. L. Magin, P. C. Lauterbur.
- RIGR Reduced encoding imaging by generalized series reconstruction
- a related technique is the two-reference RIGR (TRIGR) method, which uses two reference images instead of one.
- the Brix model assumes a central intravascular compartment and a peripheral extravascular/extracellular compartment.
- the input of a contrast agent into the intravascular compartment is considered to be equal to the infusion rate of the contrast agent.
- the elimination of contrast agent occurs only through the central intravascular compartment, with a first-order rate constant.
- the Larsson model is similar to the Brix model in that it is also based on the contrast material exchange between the capillary bed and the extracellular matrix, with exclusion from the intracellular compartment.
- the Tofts model for Gd-based dynamic contrast-enhanced analysis was originally developed to measure changes in the blood-brain barrier. Time-dependent changes in the concentration of the contrast agent are assumed to be determined by its rate of exchange between the capillaries and the extracellular tissue spaces following the concentration gradient between these two compartments.
- a further advantage of the present invention is that high-resolution parametric images of physiologic tissue parameters can be produced. Further, the present invention enables medical personnel to accurately determine pharmacokinetic parameters, such as vascular permeability, in fast-enhancing tissues. Moreover, prostate MRI and subsequent pharmacokinetic analysis can be performed using scanners with limited gradient strength, such as 1.5 T MRI scanners, without the use of an endorectal coil, thereby increasing patient comfort and willingness to undergo the imaging procedure.
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US20090190806A1 (en) | 2009-07-30 |
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